INTRAGUILD PREDATION DRIVES EVOLUTIONARY NICHE SHIFT IN THREESPINE STICKLEBACK
Bibliographic record
Abstract
Intraguild predation--competition and predation by the same antagonist--is widespread, but its evolutionary consequences are unknown. Intraguild prey may evolve antipredator defenses, superior competitive ability on shared resources, or the ability to use an alternative resource, any of which may alter the structure of the food web. We tested for evolutionary responses by threespine stickleback to a benthic intraguild predator, prickly sculpin. We used a comparative morphometric analysis to show that stickleback sympatric with sculpin are more armored and have more limnetic-like body shapes than allopatric stickleback. To test the ecological implications of this shift, we conducted a mesocosm experiment that varied sculpin presence and stickleback population of origin (from one sympatric and one allopatric lake). Predation by sculpin greatly increased the mortality of allopatric stickleback. In contrast, sculpin presence did not affect the mortality of sympatric stickleback, although they did have lower growth rates suggesting increased nonpredatory effects of sculpin. Consistent with their morphology, sympatric stickleback included more pelagic prey in their diets, leading to depletion of zooplankton in the mesocosms. These findings suggest that intraguild prey evolution has altered food web structure by reducing both predation by the intraguild predator and diet overlap between species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".